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| United States Patent Application |
20090281741
|
| Kind Code
|
A1
|
|
van Zyl; Gideon J.
|
November 12, 2009
|
SYSTEM, METHOD, AND APPARATUS FOR MONITORING POWER
Abstract
A system, method and apparatus for monitoring a processing system is
disclosed. The method includes obtaining N parameter-value pairs that
include a first parameter value and a second parameter value; obtaining,
for each parameter-value pair, the product of the first parameter value
and the complex conjugate of the second parameter value to obtain N
products defined by a real part and an imaginary part; obtaining, for
each parameter-value pair, a product of the second parameter value and
the complex conjugate of the second parameter value to obtain N real
numbers; calculating an average reflection coefficient by dividing an
imaginary number by an average of the N real numbers, the real component
of the imaginary number being equal to the average of the real parts of
the N products and the imaginary part of the imaginary number being equal
to an average of the imaginary parts of the N products.
| Inventors: |
van Zyl; Gideon J.; (Fort Collins, CO)
|
| Correspondence Address:
|
Neugeboren O'Dowd PC
1227 Spruce Street, SUITE 200
BOULDER
CO
80302
US
|
| Serial No.:
|
116375 |
| Series Code:
|
12
|
| Filed:
|
May 7, 2008 |
| Current U.S. Class: |
702/60 |
| Class at Publication: |
702/60 |
| International Class: |
G01R 21/00 20060101 G01R021/00 |
Claims
1. A method for monitoring a processing system, comprising:sampling RF
power that is applied to a plasma load to obtain N parameter-value pairs,
each of the parameter-value pairs including a first parameter value and a
second parameter value;obtaining, for each parameter-value pair, the
product of the first parameter value and the complex conjugate of the
second parameter value to obtain N products, each of the N products
defined by a real part and an imaginary part;obtaining, for each
parameter-value pair, a product of the second parameter value and the
complex conjugate of the second parameter value to obtain N real
numbers;calculating an average reflection coefficient .GAMMA., the
average reflection coefficient .GAMMA. being defined by the equation:
.GAMMA. = < a > + < b > j < r > ##EQU00005##
wherein <a> is an average of the real parts of the N products,
<b> is an average of the imaginary parts of the N products and
<r> is an average of the N real numbers; andutilizing the average
reflection coefficient .GAMMA. to manage the processing system.
2. The method of claim 1, wherein the first parameter value includes a
reflected voltage value and the second parameter value includes a forward
voltage value.
3. The method of claim 1, wherein the first parameter includes a current
value, and the second parameter includes a voltage value.
4. The method of claim 1, including:digitizing the sampled RF power to
obtain a stream of digital RF signals,down-converting, for each of a
plurality of particular frequencies, the stream of digital RF signals to
obtain N parameter-value pairs for each of the plurality of particular
frequencies.
5. The method of claim 1, including sampling the RF power at an output of
an RF generator supplying power to the plasma load.
6. The method of claim 1, including sampling the RF power at an input to a
plasma chamber that contains the plasma load.
7. An apparatus for monitoring power applied to a plasma load comprising:a
first input configured to receive RF samples of power that is applied to
the plasma load, the RF samples including information indicative of N
parameter-value pairs, each of the N parameter-value pairs including a
first parameter value and a second parameter value;a reflection
coefficient module configured to:obtain, for each parameter-value pair,
the product of the first parameter value and the complex conjugate of the
second parameter value to obtain N products, each of the N products
defined by a real part and an imaginary part;obtaining, for each
parameter-value pair, a product of the second parameter value and the
complex conjugate of the second parameter value to obtain N real
numbers;calculating an average reflection coefficient .GAMMA., the
average reflection coefficient .GAMMA. being defined by the equation:
.GAMMA. = < a > + < b > j < r > ##EQU00006##
wherein <a> is an average of the real parts of the N products,
<b> is an average of the imaginary parts of the N products and
<r> is an average of the N real numbers.
8. The apparatus of claim 7, wherein the reflection coefficient module
includes a processor and memory, and wherein the processor is configured
to execute processor-readable instructions to calculate the average
reflection coefficient .GAMMA..
9. The apparatus of claim 7, wherein the first parameter value includes a
reflected voltage value and the second parameter value includes a forward
voltage value.
10. The apparatus of claim 7, wherein the first parameter includes a
current value, and the second parameter includes a voltage value.
11. The apparatus of claim 7, including:an analog to digital converter
configured to digitizing the sampled RF power to obtain a stream of
digital RF signals, the digital RF signals including N digital
parameter-value pairs.
12. The apparatus of claim 7, including a display configured to display
the average reflection coefficient.
Description
FIELD OF THE INVENTION
[0001]This invention relates generally to apparatus and methods for plasma
processing, and more particularly to apparatus and methods for monitoring
parameters of plasma processing systems.
BACKGROUND OF THE INVENTION
[0002]In plasma processing applications, such as the manufacture of
semiconductors or flat panel displays, RF power generators apply a
voltage to a load in a plasma chamber and may operate over a wide range
of frequencies. The impedance of a processing plasma can vary with the
frequency of this applied voltage, chamber pressure, gas composition, and
the target or substrate material. And the impedance of the plasma load
affects the efficiency at which power is applied from the generator to
the load. Consequently, an estimate of the plasma load impedance is a
parameter that is often desirable for users to have available.
[0003]Obtaining a good estimate of load impedance, however, is often
difficult. For example, accurate measurements of forward and reflected
power, more precisely the incident and reflected signals who's magnitudes
squared are proportional to forward and reflected power, as well as the
phase relationship between the forward and reflected signals may be
utilized to obtain an estimate of load impedance, but when the
measurement system (the measurement system to obtain forward and
reflected signals) is not synchronized with a reference oscillator (e.g.,
an oscillator of the RF generator), each sampled measurement of forward
and reflected power may potentially have a random phase with respect to
the reference oscillator. As a consequence, it is very difficult, if not
impossible, to average either the forward voltage or the reflected
voltage measurements (e.g., to remove noise and unwanted modulation).
[0004]To illustrate the problem, consider a simple measurement system such
as shown in FIG. 1A containing a sensor such as a directional coupler or
voltage/current (VI) sensor. It can be shown that almost any linear four
port network can be used as a sensor for determining forward and
reflected power as well as load impedance. Such a sensor is perfectly
correctable in the sense that there are four complex numbers such that
[ V forward V reflected ] = [ k 11 k 12
k 21 k 22 ] [ V 3 V 4 ] ##EQU00001## as
long as ##EQU00001.2## S 13 , S 24 .noteq. S 14 ,
S 23 ##EQU00001.3##
[0005]where S.sub.ij, i, j.epsilon.{1,2} are the scattering parameters (S
parameters) of the sensor with the ports numbered as in FIG. 1A. In the
above matrix equation V.sub.forward and V.sub.reflected are the corrected
forward and reflected signals with respect to a 50'.OMEGA. reference
impedance such that the forward power is equal to |V.sub.forward|.sup.2,
the reflected power is equal to |V.sub.reflected|.sup.2 and the load
reflection coefficient, .rho..sub.load, is equal to
V.sub.reflected/V.sub.forward. The load reflection coefficient in turn is
related to the load impedance by
Z load = 50 1 + .rho. load 1 - .rho. load .
##EQU00002##
[0006]The entries in the matrix, k.sub.11, k.sub.12, k.sub.21 and k.sub.22
can be calculated from the scattering parameters of the sensor and the
impedance presented to the sensor at the sense ports. Any one of the
entries, typically k.sub.11 can be made real by multiplying through with
a suitable complex number. Normally the entries are determined by
calibrating the entire system. Such calibration can be performed by
measuring the response of the sensor system to at least three impedances
and using a power standard to scale the matrix correctly. Note that all
numbers involved are complex numbers representing the magnitude and phase
of the signals in a convenient mathematical form. Thus, with t
representing time and choosing an arbitrary instant in time to correspond
to t=0, the signal V.sub.3 in the matrix equation is related to the time
domain signal at port 3 of the sensor, .nu.3, by the equation:
.nu..sub.3(t)=V.sub.3e.sup.j.omega..sup.0.sup.t+V*.sub.3e.sup.-j.omega..su-
p.0.sup.t
[0007]where .omega..sub.0 is the frequency of the source in rad/s and x*
represents the complex conjugate of x. The same holds true for V.sub.4,
V.sub.forward and V.sub.reflected. As shown in FIG. 1A estimates of
V.sub.3 and V.sub.4 can be obtained by simply taking samples of
.nu..sub.3 and .nu..sub.4 90 degrees apart with 90 degrees corresponding
to a delay of one fourth of the period of the source. A simple
measurement system such as shown in FIG. 1A assumes a pure sinusoidal
source. In general, a more complex system incorporating filters and more
sophisticated and less noisy estimates of the phasors V.sub.3 and V.sub.4
are used. As illustrated in FIGS. 1B and 1C, unless the samples to
estimate V.sub.3 and V.sub.4 are perfectly synchronized with the
frequency of the source, samples of V.sub.3 and V.sub.4 taken at
different times are rotated. In FIG. 1B, a(1)+jb(1) illustrates a sample
of V.sub.3 taken at time t.sub.1, c(1)+jd(1) illustrates a sample of
V.sub.4 taken at time t.sub.1, and in FIG. 1C, a(2)+jb(2) illustrates a
sample of V.sub.3 taken at time t.sub.2, and c(2)+jd(2) illustrates a
sample of V.sub.4 taken at time t.sub.2.
[0008]As shown in this illustration, the magnitudes of the samples of
V.sub.3 and V.sub.4 and well as the phase relationship between V.sub.3
and V.sub.4 are determined by the power delivered to the load and the
load impedance and do not change under steady state excitation, but the
samples are rotated with respect to each other except in the special case
where the sampling times are perfectly synchronized with the frequency of
the source and taken exactly one or multiples of one cycle apart. The
same is true for samples of the corrected forward and reflected signals
V.sub.forward and V.sub.reflected. If averaging is used it can be applied
to either the uncorrected signals V.sub.3 and V.sub.4 or the corrected
signals V.sub.forward and V.sub.reflected. The choice between averaging
depends on the available computational resources. It is often possible to
calculate the corrected signals and carry out averaging on the corrected
signals, but if computational resources are really limited it may be more
advantageous to average the uncorrected signals V.sub.3 and V.sub.4 and
perform slightly more computations at a much reduced rate to obtain the
corrected signals from the averaged uncorrected signals.
[0009]One approach to deal with the problem of random phase in power
measurements includes calculating, for each sampled pair of forward and
reflected signals, a reflection coefficient, which is equal to the ratio
of the reflected signal to the forward signal. Then the set of calculated
reflection coefficients is averaged to obtain an average reflection
coefficient value. For example, in one millisecond, a thousand
measurements of forward and reflected signals may be taken, and as a
consequence, a thousand division operations (e.g., uncorrected reflected
signal V.sub.4(k) divided by uncorrected forward signal V.sub.3(k),
k.epsilon.{1, 2, . . . }) are carried out in each millisecond to obtain a
set of reflection coefficient values that are then averaged to obtain an
average reflection coefficient. Problematically, each time a reflection
coefficient is calculated in this manner, system resources are utilized;
thus this approach to obtaining an average reflection coefficient is
computationally intensive and is prone to excessive utilization of system
resources.
[0010]As a consequence, known techniques are often too inefficient to
provide desirable information about the electrical characteristics of
plasma loads. Accordingly, a system and method are needed to address the
shortfalls of present technology and to provide other new and innovative
features.
SUMMARY OF THE INVENTION
[0011]Exemplary embodiments of the present invention that are shown in the
drawings are summarized below. These and other embodiments are more fully
described in the Detailed Description section. It is to be understood,
however, that there is no intention to limit the invention to the forms
described in this Summary of the Invention or in the Detailed
Description. One skilled in the art can recognize that there are numerous
modifications, equivalents and alternative constructions that fall within
the spirit and scope of the invention as expressed in the claims.
[0012]Embodiments of the present invention can provide a system, method
and apparatus for monitoring a processing system. The method, for
example, may include sampling RF power that is applied to a plasma load
to obtain N parameter-value pairs, each of the parameter-value pairs
including a first parameter value and a second parameter value;
obtaining, for each parameter-value pair, the product of the first
parameter value and the complex conjugate of the second parameter value
to obtain N products, each of the N products defined by a real part and
an imaginary part; obtaining, for each parameter-value pair, a product of
the second parameter value and the complex conjugate of the second
parameter value to obtain N real numbers; calculating an average
reflection coefficient .GAMMA., the average reflection coefficient
.GAMMA. being defined by the equation:
.GAMMA. = < a > + < b > j < r > ##EQU00003##
wherein <a> is an average of the real parts of the N products,
<b> is an average of the imaginary parts of the N products and
<r> is an average of the N real numbers; and utilizing the average
reflection coefficient .GAMMA. to manage the processing system.
[0013]As previously stated, the above-described embodiments and
implementations are for illustration purposes only. Numerous other
embodiments, implementations, and details of the invention are easily
recognized by those of skill in the art from the following descriptions
and claims.
BRIEF DESCRIPTION OF THE DRAWINGS
[0014]Various objects and advantages and a more complete understanding of
the present invention are apparent and more readily appreciated by
reference to the following Detailed Description and to the appended
claims when taken in conjunction with the accompanying Drawings wherein:
[0015]FIGS. 1A, 1B, and 1C are a block diagram of a simple measurement
system, a graph depicting voltage samples taken with the system of FIG.
1A at a first time, and a graph depicting voltage samples taken with the
system of FIG. 1A at a second time, respectively;
[0016]FIG. 2 is a block diagram depicting a plasma processing environment
in which several embodiments of the invention may be implemented;
[0017]FIG. 3 is a block diagram depicting an exemplary embodiment of a
processing portion of the sensors described with reference to FIG. 2;
[0018]FIG. 4 is a flowchart that depicts an exemplary method for
monitoring power that is applied to a plasma load;
[0019]FIG. 5 is a block diagram depicting an exemplary embodiment of the
transform portion depicted in FIG. 3;
[0020]FIG. 6 is a flowchart depicting an exemplary method for performing a
transform of sampled RF data;
[0021]FIG. 7 is a block diagram depicting functional components, which may
be utilized to realize the reflection coefficient module described with
reference to FIG. 3; and
[0022]FIG. 8 is a flowchart depicting an exemplary method for calculating
an average reflection coefficient, which may be utilized in connection
with many embodiments.
DETAILED DESCRIPTION
[0023]Referring now to the drawings, where like or similar elements are
designated with identical reference numerals throughout the several
views, and referring in particular to FIG. 2, it is a block diagram
depicting a plasma processing environment 100 in which several
embodiments of the invention may be implemented. As shown, a radio
frequency (RF) generator 102 is coupled to a plasma chamber 104 via an
impedance matching network 106, and an analysis portion 108 is disposed
to receive an input from a first sensor 110 that is coupled to an output
of the RF generator 102 and in input from a second sensor 112 that is
coupled to an input of the plasma chamber 104. As depicted, the analysis
portion 108 is also coupled to a man-machine interface 114, which may
include a keyboard, display and pointing device (e.g., a mouse).
[0024]The illustrated arrangement of these components is logical and not
meant to be an actual hardware diagram; thus, the components can be
combined or further separated in an actual implementation. For example,
the functionality of one or both of the sensors 110, 112 may be
implemented with components of the analysis portion 108, the sensor 110
may be entirely contained within a housing of the generator 102, and in
some implementations, either of the sensors 110, 112 may be omitted from
the system 100. Moreover, it should be recognized that the components
included in FIG. 2 depict an exemplary implementation, and in other
embodiments, as discussed further herein, some components may be omitted
and/or other components added.
[0025]The RF power generator 102 generally provides RF power to the plasma
chamber 104 to ignite and sustain a plasma in the chamber 104 for plasma
processing. Although not required, in many embodiments the RF generator
102 is realized by a collection of two or more RF generators, and each of
the RF generators provides power at a different frequency. Although
certainly not required, the RF generator 102 may be realized by one or
more PARAMOUNT model RF generators available from Advanced Energy
Incorporated in Fort Collins, Colo.
[0026]The matching network 106 in this embodiment is generally configured
to transform the chamber impedance, which can vary with the frequency of
this applied voltage, chamber pressure, gas composition, and the target
or substrate material, to an ideal load for the RF power generator 102.
One of ordinary skill in the art will appreciate that a variety of
different matching network types may be utilized for this purpose. The
matching network 106 may be realized by a NAVIGATOR model digital
impedance matching network available from Advanced Energy Incorporated in
Fort Collins, Colo., but other impendence matching networks may also be
utilized.
[0027]The first sensor 110 in this embodiment is generally configured to
measure one or more parameters of the power applied by the generator
(e.g., forward power, reflected power, voltage, and/or current). As
discussed further herein, the measured parameters may be utilized to
obtain an estimate of load impedance (e.g., an impedance of the plasma in
the chamber 104), which may be reported to the analysis portion for
reporting, via the man-machine interface 114, to a user. Additionally,
the measures parameters may be utilized to close feedback to the RF
generator 102 (e.g., based upon a difference between the measured
parameter and a set point.)
[0028]The second sensor 112 in the embodiment depicted in FIG. 2 may be
generally configured to provide a characterization of the plasma in the
chamber 104. For example, measurements taken by the sensor 112 may be
used to estimate ion energy distribution, electron density, and/or energy
distribution, which directly impact results of the processing in the
chamber 104. In many embodiments, by way of further example, electrical
characteristics (e.g., voltage, current, impedance) measured at an input
111 to the chamber 104 can be used to predict values of associated plasma
parameters. For example, measurements from the second sensor 112 may be
used in connection with known information (e.g., information indicating
how a deviation from a particular voltage would, or would not, affect one
or more plasma parameter(s)). Although not depicted in FIG. 2, the
sensors 110, 112 may include a transducer, electronics, and processing
logic (e.g., instructions embodied in software, hardware, firmware or a
combination thereof).
[0029]In many embodiments (e.g., as discussed in more detail further
herein), the samples taken by the sensor 100 and/or sensor 112 are
digitized and then analyzed in the digital domain. In other embodiments,
however, the sampled parameter values are analyzed in the analog domain.
[0030]The analysis portion 108 is generally configured to receive
information (e.g., information about parameters of power) from the
sensors 110, 112 and convey the information to a user via the man-machine
interface 114. The analysis portion 108 may be realized by a general
purpose computer in connection with software, or dedicated hardware
and/or firmware.
[0031]Referring next to FIG. 3, shown is an exemplary embodiment of a
processing portion 200, which may be implemented as a portion of one or
more of the sensors 110, 112, RF power generator 102, the matching
network 106 and the analysis portion 108 described with reference to FIG.
3. By way of example, the functional components depicted in FIG. 3 may be
entirely contained within one component (e.g., the RF generator 102 or
the sensors 110, 112) or may be distributed among one or more of the
other components described with reference to FIG. 3. As shown, the
processing portion 200 in this embodiment includes a first and second
processing chains 202, 204, and each processing chain 202, 204 includes
an analog front end 206, an analog to digital (A/D) converter 208, a
transform portion 210, and a correction portion 212.
[0032]The depiction of components in FIG. 3 is logical and not meant to be
an actual hardware diagram; thus, the components can be combined or
further separated in an actual implementation. For example, the A/D
converter 208 may be realized by two separate A/D converters (e.g., 14
bit converters), and the transform portion 210 may be realized by a
collection of hardware, firmware, and/or software components. In
addition, it is contemplated that the reflection coefficient module 222
may be realized by components that are separate from other components of
the processing portion 200. In one particular embodiment for example, the
transform and correction portions 210, 212 are realized by a field
programmable gate array and the reflection coefficient module 222 is
realized by a processor in connection with processor-executable code.
[0033]In the exemplary embodiment depicted in FIG. 3, the first and second
processing chains 202, 204 are configured to receive respective
forward-voltage and reverse-voltage analog-RF signals (e.g., from a
directional coupler, which may be referred to as a forward and reflected
wave sensor). In other embodiments the first and second processing chains
202, 204 may receive voltage and current analog-RF signals. For clarity,
the operation of the processing portion 200 is described with reference
to a single processing chain, but it should be recognized that
corresponding functions in a second processing chain are carried out.
[0034]While referring to FIG. 3, simultaneous reference will be made to
FIG. 4, which is a flowchart 300 that depicts an exemplary method for
monitoring power that is applied to a plasma load. It should be
recognized, however, that the method depicted in FIG. 4 is not limited to
the specific embodiment depicted in FIG. 3. As shown in FIG. 4, RF power
that is generated by an RF generator (e.g., the RF generator 102) is
sampled to obtain RF signals that include information indicative of power
at a plurality of particular frequencies that fall within a frequency
range (Blocks 300, 302).
[0035]For example, the frequency range may include the range of
frequencies from 400 kHz to 60 MHz, but this range may certainly vary
depending upon, for example, the frequencies of the RF generator(s) that
provide power to the system. The plurality of particular frequencies may
be frequencies of a particular interest, and these frequencies, as
discussed further herein, may also vary depending upon the frequencies of
power that are applied to a processing chamber (e.g., processing chamber
104). For example, particular frequencies may be fundamental frequencies,
second and third harmonics of each of the frequencies; and
intermodulation frequencies.
[0036]As shown with reference to FIG. 3, the analog front end 206 of the
first processing chain 202 is configured to receive a forward-voltage
analog-RF signal from a transducer (not shown) and prepare the analog RF
signal for digital conversion. The analog front end 206, for example, may
include a voltage divider and prefilter. As shown, once the analog-RF
signal is processed by the analog front end 206, it is digitized by the
A/D converter 208 to generate a stream of digital RF signals that
includes the information indicative of power at the plurality of
particular frequencies (Block 306). In some embodiments for example, 64
million samples are taken of the analog-RF signal per second with 14-bit
accuracy.
[0037]As shown, once the sampled RF signals are digitized, the information
indicative of power (in digital form) is successively transformed, for
each of the plurality of particular frequencies, from a time domain into
a frequency domain (Block 308). As an example, the transform portion 210
depicted in FIG. 3 receives the streams of digital RF signals 214, 216
and successively transforms the information in each of the digital
streams 214, 216 from a time domain to a frequency domain, and provides
both in-phase and quadrature information for both the forward voltage
stream and the reflected voltage steam.
[0038]Although not required, the transform portion 210 in some embodiments
is realized by a field programmable gate array (FPGA), which is
programmed to carry out, at a first moment in time, a fourier transform
(e.g., a digital fourier transform ((DFT)) at one frequency, and then
carry out a fourier transform, at a subsequent moment in time, at another
frequency so that fourier transforms are successively carried out, one
frequency at a time. Beneficially, this approach is faster and more
accurate that attempting to take a fourier transform over the entire
range of frequencies (e.g., from 400 kHz to 60 MHz) as is done in prior
solutions.
[0039]In the embodiment depicted in FIG. 3, the particular frequencies
f.sub.1-N at which successive transforms of the digital RF signals are
taken are stored in a table 218 that is accessible by the transform
portion 210. In variations of this embodiment, a user is able to enter
the particular frequencies f.sub.1-N (e.g., using the man-machine
interface 114 or other input means). The particular frequencies f.sub.1-N
entered may be frequencies of interest because, for example, the
frequencies affect one or more plasma parameters. As an example, if two
frequencies are applied to a chamber (e.g., utilizing two generators),
there may be 8 frequencies of interest: the two fundamental frequencies;
the second and third harmonics of each of the frequencies; and the two
intermodulation products of the two frequencies.
[0040]In some embodiments, 256 samples of each of the digital streams 214,
216 are utilized to generate a Fourier transform, and in many embodiments
the data rate of the digital streams 214, 216 is 64 Mbs. It is
contemplated, however, that the number of samples may be increased (e.g.,
to improve accuracy) or decreased (e.g., to increase the rate at which
information in the streams is transformed). Beneficially, in many
implementations of the transform portion 210, the digital streams 214,
216 are continuous data streams (e.g., there is no buffering of the data)
so that a transform, at each of the particular frequencies (e.g.,
frequencies f.sub.1-N) is quickly carried out (e.g., every micro second).
[0041]As shown in the embodiment depicted in FIG. 2, the transform portion
210 provides two outputs (e.g., in phase information and quadrature
information) for each of the digital forward and reflected voltage
streams 214, 216, and each of the four values are then corrected by the
correction portion 212. As depicted in FIG. 3, in some embodiments,
correction matrices 220 are utilized to correct the transformed
information from the transform portion 210. For example, each of the four
values provided by the transform portion 210 are multiplied by a
correction matrix that is stored in memory (e.g., non-volatile memory).
[0042]In many embodiments the matrices 220 are the result of a calibration
process in which known signals are measured and correction factors are
generated to correct for inaccuracies in a sensor. In one embodiment, the
memory includes one matrix for each of 125 megahertz, and each of the
matrices is a 2.times.4 matrix. And in variations, a separate matrix is
used for each of impedance and power; thus 250, 2.times.4 matrices are
utilized in some variations. As shown, after correction by the correction
portion 212, four outputs, representing corrected in-phase and quadrature
representations of forward and reflected voltage are output and provided
to a reflection coefficient module 222.
[0043]In this embodiment, the reflection coefficient module 222 receives
values for both forward and reflected voltage from the correction portion
212 and calculates a reflection coefficient (e.g., an average reflection
coefficient) that may be utilized to estimate an impedance of the plasma
load. Although not required, the reflection coefficient module 222 may be
realized by executable code (e.g., embodied in software) that is executed
by a microprocessor. And the computational resources required to
calculate the average reflection coefficient may be reduced by a novel
approach discussed further herein.
[0044]In some embodiments, a look-up table (e.g., of sine and cosine
functions) is utilized to carry out a fourier transform in the transform
portion 210. Although fourier transforms may be carried out relatively
quickly using this methodology, the amount of stored data may be unwieldy
when a relatively high accuracy is required.
[0045]In other embodiments, direct digital synthesis (DDS) is utilized in
connection with the transform of data. Referring to FIG. 5, for example,
it is a block diagram depicting an exemplary embodiment of the transform
portion 210 depicted in FIG. 2. While referring to FIG. 5, simultaneous
reference will be made to FIG. 6, which is a flowchart depicting an
exemplary method for performing a transform of sampled RF data. As shown,
in the exemplary embodiment depicted in FIG. 5, a particular frequency is
selected (e.g., one of the particular frequencies f.sub.1-N described
with reference to FIG. 3) (Blocks 500, 502), and a direct digital
synthesis portion 402 synthesizes a sinusoidal function for the frequency
Block 504). In the embodiment depicted in FIG. 5, for example, both a
sine and a cosine function are synthesized.
[0046]As shown, a sample indicative of an RF power parameter is obtained
(Block 506). In the exemplary embodiment depicted in FIG. 5, digital
samples 414, 416 of both forward and reflected voltage are obtained, but
in other embodiments other parameters are obtained (e.g., voltage and
current). As shown in FIG. 6, for each selected frequency, products of
the sinusoidal function at the selected frequency and multiple samples of
the RF data are generated (Block 508). In the embodiment depicted in FIG.
5 for example, after a windowing function 404 is carried out on the
digital RF samples 414, 416 (e.g., obtained from the A/D converter), the
sine and cosine functions generated by the DDS 402 are multiplied by each
sample by multipliers in a digital fourier transform portion 406.
[0047]As shown, the products of the sinusoidal function and the samples
are accumulated (Block 510) (e.g., by accumulators in the digital fourier
transform portion 406), and once a desired number of digital RF samples
are utilized (Block 512), a normalized value of the accumulated products
is provided (Block 514). In some embodiments 64 samples are utilized and
in other embodiments 256 are utilized. In yet other embodiments other
numbers of digital RF samples are utilized to obtain the value of a
parameter (e.g., forward or reflected voltage) at a particular frequency.
[0048]As shown in FIG. 6, for each particular frequency (e.g., each of the
N frequencies in table 218) Blocks 502-514 are carried out so that a
transforms of the sampled RF data are successively carried out for each
frequency of interest. In one embodiment, the DDS 402, windowing 404 and
DFT 406 portions are realized by an FPGA. But this is certainly not
required, and in other embodiments the DDS portion 402 is realized by
dedicated chip and the windowing 404 and DFT 406 portions are implemented
separately (e.g., by an FPGA).
[0049]Referring next to FIG. 7, shown is a block diagram depicting
functional components of an exemplary reflection coefficient module 600
that may be used to realize the reflection coefficient module 222
described with reference to FIG. 2. While referring to FIG. 7,
simultaneous reference will be made to FIG. 8, which is a flow chart
depicting an exemplary method that may be utilized in connection with the
reflection coefficient module 600.
[0050]The depiction of components in FIG. 7 is logical and not meant to be
an actual hardware diagram; thus, the components can be combined or
further separated in an actual implementation. The components depicted in
FIG. 600 may be realized by a collection of hardware, firmware, and/or
software components. In one particular embodiment for example, the
reflection coefficient module 600 is realized by software that is
executed by a microprocessor.
[0051]As shown, the reflection coefficient module 600 initially receives N
parameter-value pairs, and each of the parameter-value pairs including a
first parameter value (e.g., reflected voltage) and a second parameter
value (e.g., forward voltage) obtained from samples of RF power that is
applied to a plasma load (Blocks 700, 702). In some embodiments, the
parameter-value pairs (e.g., forward and reflected voltage values) are
obtained utilizing one or more of the process(es) described with
reference to FIGS. 3-6, but in other embodiments, other known techniques
for obtaining values of a pair of parameters are utilized.
[0052]As depicted in FIG. 8, the product of the first parameter value and
the complex conjugate of the second parameter value are then utilized to
obtain N products. Referring to FIG. 7 for example, a complex conjugate
of forward voltage is determined by a complex conjugate portion 602 and
the complex conjugate of the forward voltage is provided to a multiplier
604, which multiplies the complex conjugate of the forward voltage times
the reflected voltage to provide N products that are each defined by a
real portion a and an imaginary portion b.
[0053]In addition, for each parameter-value pair, a product of the second
parameter value and the complex conjugate of the second parameter value
are utilized to obtain N real numbers (Block 708). Referring again to
FIG. 7, a multiplier 606 receives and multiplies the forward voltage and
the complex conjugate of the forward voltage to obtain N real numbers r.
[0054]As shown in FIG. 8, an average reflection coefficient is then
calculated as follows in Equation 1:
.GAMMA. = < a > + < b > j < r > ##EQU00004##
wherein <a> is an average of the real parts of the N products,
<b> is an average of the imaginary parts of the N products and
<r> is an average of the N real numbers (Block 710). As depicted in
FIG. 7 for example, the real parts a of the N products are averaged by
accumulator 608; the imaginary parts b of the N products are average by
accumulator 610; and the N real numbers r are averaged by accumulator
612. And the divider 614 provides the average reflection coefficient in
accordance with Equation 1. The average reflection coefficient may then
be used in connection with management of the processing system. For
example, the average reflection coefficient may be provided to a user of
the processing system, may used to calibrate the system, and may be used
in connection with matching the plasma load with the impedance of the
generator.
[0055]Beneficially, the structure and method used to arrive at an average
reflection coefficient outlined with reference to FIGS. 7 and 8 requires
only two division operations (e.g., one division calculates
<a>/<r> for the real part and the other division calculates
<b>/<r> for the imaginary part) for a given sample window
(e.g., one millisecond) as opposed to known techniques that require
hundreds of computationally intensive division operations (e.g., of each
reflected power sample by each forward power sample) over the same sample
window. As a consequence, the structure and method described with
reference to FIGS. 7 and 8 enables an average reflection coefficient to
be calculated with fewer system resources than known techniques.
[0056]In conclusion, the present invention provides, among other things, a
system and method for monitoring a processing system. Those skilled in
the art can readily recognize that numerous variations and substitutions
may be made in the invention, its use and its configuration to achieve
substantially the same results as achieved by the embodiments described
herein. Accordingly, there is no intention to limit the invention to the
disclosed exemplary forms. Many variations, modifications and alternative
constructions fall within the scope and spirit of the disclosed invention
as expressed in the claims.
* * * * *